Abstract
The use of mass spectrometry (MS) in clinical diagnostics has progressed due to its sensitivity,selectivity, specificity, speed of analysis, and ability to reduce false positives and false
negatives when providing a diagnosis for a patient. This project has used these benefits of MS
performance to rapidly analyse several compounds with different physicochemical properties
from a single extraction and UPLC-MS method in a short period of time.
This research emphasizes the importance of using high-resolution accurate mass (HRAM)
instruments, such as Q-ToF mass spectrometers, in LC-MS method development. Unlike triple
quadrupole instruments that act as filters, HRAM instruments enable the detection of co-eluting
compounds that may affect quantification accuracy. In this study, we applied HRAM to analyse
alcohol metabolites and observed a co-eluting compound with a similar mass-to-charge ratio
(m/z) to the target molecules, which can significantly impact quantification results. This finding
highlights the potential issue of co-elution when using industry-standard separation methods
with triple quadrupole instruments, which many researchers may be unaware of. By employing
HRAM, clear separation of target compounds was achieved, facilitating accurate
quantification. The HRAM approach offers enhanced sensitivity, selectivity, and a
comprehensive understanding of sample composition, benefiting fields requiring precise
quantification.
The compounds chosen for this study included alcohol metabolites (phosphatidylethanol),
nicotine and its common metabolites, tramadol, diazepam, and alprazolam and their common
metabolites. Results obtained demonstrate that the newly developed method is suitable to
identify and quantify the molecules that enable patients to be categorised as heavy, moderate,
and low alcohol drinkers, nicotine smokers, and patients who are non-compliant with their
prescribed medication. The lower limit of quantification was 10 ng/mL, with the lower limit of
detection ranging between 2 ng/mL and 10 ng/mL which covers the clinically relevant levels.
The percentage recovery for all the selected compounds fell within the range of 74% to 115%
across the clinically relevant concentration range. Accuracy and precision of percentage
recoveries of target analytes were observed within the ranges of 18% to 15% and 0.9% to 26%,
respectively.
In the exploration of direct analysis methods, the focus was on removing complexity and
reducing the time required for analysis. Direct analysis mass spectrometry (MS) techniques
were employed to identify target analytes at clinically relevant levels. The analysis focused on
nicotine and its metabolites in horse blood, chosen as the biofluid of interest. By using the
ASAP-QDa technique, successful identification of nicotine and its metabolites at clinically
relevant levels was achieved. This method proved suitable for distinguishing heavy and
moderate nicotine smokers through a semi-quantitative profiling approach using a deuterated
internal standard. The lower limit of detection, even in the presence of the matrix, was
determined to be 250 ng/mL for cotinine and trans-3'-hydroxycotinine. Additionally, direct
infusion cyclic ion mobility was applied to analyse alcohol and nicotine metabolites. This
approach facilitated the accurate identification of alcohol and nicotine metabolites, enabling
differentiation between heavy alcohol drinkers and nicotine smokers. Notably, cyclic ion
mobility, particularly through the implementation of slicing, allowed for the isolation of
alcohol metabolites from the matrix. Moreover, it enhanced the signal-to-noise ratio threefold,
thereby improving sensitivity and detection capabilities. In a proof-of-principle application,
concentrations of 250 ng/mL were tested for all metabolites, demonstrating the method's
potential for rapid identification and semi-quantitative profiling. Overall, the findings highlight
the effectiveness of direct analysis techniques in analysing alcohol and nicotine metabolites,
providing a streamlined and efficient approach for identifying heavy alcohol drinkers and
nicotine smokers. This has the potential to support medical professionals in monitoring patient
treatment plans and enhancing point-of-care clinical diagnostics.
| Date of Award | 9 Oct 2024 |
|---|---|
| Original language | English |
| Awarding Institution |
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| Supervisor | Jim Scrivens (Supervisor), Safwan Akram (Supervisor), Jackie Mosely (Supervisor) & Meez Islam (Supervisor) |